A number of techniques have been developed to improve the speed and accuracy of digital communications. For example, a number of techniques have been proposed or suggested to compensate for the distortion that is inevitably present in a communication channel, such as equalization techniques that compensate for delay distortion and intersymbol interference.
J. G. Proakis, Digital Communications, McGraw-Hill, New York, 1989; and S. U. H. Qureshi, “Adaptive Equalization,” Proceedings of the IEEE, Vol. 73, pp. 1349-1387, September, 1985, describe a number of known techniques that equalize relatively constant communication channels and adapt to changes that occur in the transmission characteristics of transmission channels due to changes in environmental and other conditions. Decision feedback equalizers having adaptation logic, for example, track slow variations in a channel after an initial learning phase. In this mode, it is assumed that the output of a decoder is correct with high probability. Error signals based on these output signals are then used to update the coefficients of the equalizer. By the time an equalizer has been trained for a given channel, however, the channel has likely already changed and the obtained tap coefficients may no longer be sufficiently accurate for current conditions.
Many wireless and optical communication channels, including cellular telephone channels, exhibit rapid changes in transmission characteristics, thereby causing even greater difficulty in adaptively equalizing such channels. When equalizing a mobile (cellular) radio channel, for example, fast adaptation is typically required, especially at high vehicle speeds. Such channels are typically characterized by Rayleigh fading, Doppler effects and delay spread. Prior art equalization techniques do not sufficiently mitigate the effects of such rapidly changing channel conditions. While the adaptive Viterbi Algorithm uses the globally best estimates of the transmitted data to update the estimates of the channel impulse response, processing used to develop these estimates necessarily introduces considerable complexity and delay. Furthermore, in a rapidly changing channel environment, the obtained channel estimates may no longer be sufficiently accurate for currently processed symbols.
Differential modulation encoding techniques have also been employed to minimize the effects of fading. Differential modulation encoding, however, demonstrates an irreducible error rate in fading channels even with high signal-signal-to-noise ratios. In addition, a number of equalization techniques employ a pilot carrier signal to estimate the channel and minimize the effects of fading. A pilot signal of a given frequency, however, cannot accurately estimate the fading characteristics of a channel for other frequencies, since fading characteristics are generally frequency dependent.
A need therefore exists for a method and apparatus for equalizing a channel that provides an improved channel estimate without the complexity and delay of prior techniques. A further need exists for a method and apparatus for equalizing a channel that provides a channel estimate using the same time and frequency characteristics as the transmitted data.